Monitoring of PM10 and PM2.5 concentrations frequently is essential for assessing air quality and informing pollution control strategies. This study examines the effect of height on PM2.5 distribution in Hanoi using E...Monitoring of PM10 and PM2.5 concentrations frequently is essential for assessing air quality and informing pollution control strategies. This study examines the effect of height on PM2.5 distribution in Hanoi using EPA-standard methods at five rooftop locations on high-rise buildings. Results from Phase 1 (pre-pollution period) indicate a nearly 50% reduction in PM2.5 concentration, decreasing from 34.76 μg/m3 at 40 m to 13.95 μg/m3 at 336 m. In contrast, Phase 2 (pollution wave) showed relatively stable PM2.5 concentrations across heights, likely influenced by cold air masses and wind speed. MLR and MNLR analyses reveal the significant impact of meteorological factors and PM10 on PM2.5 levels, with the MNLR model accounting for 80% - 94% of the variance, outperforming the MLR model’s 50% - 80%. Employing UAVs, Lidar, and synchronized meteorological data is proposed as an advanced approach to enhance the accuracy of height-based dust concentration assessments.展开更多
文摘Monitoring of PM10 and PM2.5 concentrations frequently is essential for assessing air quality and informing pollution control strategies. This study examines the effect of height on PM2.5 distribution in Hanoi using EPA-standard methods at five rooftop locations on high-rise buildings. Results from Phase 1 (pre-pollution period) indicate a nearly 50% reduction in PM2.5 concentration, decreasing from 34.76 μg/m3 at 40 m to 13.95 μg/m3 at 336 m. In contrast, Phase 2 (pollution wave) showed relatively stable PM2.5 concentrations across heights, likely influenced by cold air masses and wind speed. MLR and MNLR analyses reveal the significant impact of meteorological factors and PM10 on PM2.5 levels, with the MNLR model accounting for 80% - 94% of the variance, outperforming the MLR model’s 50% - 80%. Employing UAVs, Lidar, and synchronized meteorological data is proposed as an advanced approach to enhance the accuracy of height-based dust concentration assessments.
